Search results for "weighting"
showing 10 items of 117 documents
Le score de propension : un guide méthodologique pour les recherches expérimentales et quasi expérimentales en éducation
2016
La méthode du score de propension devient de plus en plus populaire pour estimer les effets causaux d’un programme d’intervention. Si les applications empiriques de cette méthode sont encore rares dans les recherches en éducation, des exemples de son utilisation se trouvent aisément dans d’autres disciplines. Cependant, sa mise en place soulève plusieurs questions. L’objectif de cet article est de fournir des éléments de réponses guidant le chercheur et l’évaluateur du domaine de l’éducation pour l’estimation et l’utilisation du score de propension. Les différentes étapes de son application sont présentées pas à pas : évaluation du biais de sélection, construction du score de propension et …
Modeling user preferences in content-based image retrieval: A novel attempt to bridge the semantic gap
2015
This paper is concerned with content-based image retrieval from a stochastic point of view. The semantic gap problem is addressed in two ways. First, a dimensional reduction is applied using the (pre-calculated) distances among images. The dimension of the reduced vector is the number of preferences that we allow the user to choose from, in this case, three levels. Second, the conditional probability distribution of the random user preference, given this reduced feature vector, is modeled using a proportional odds model. A new model is fitted at each iteration. The score used to rank the image database is based on the estimated probability function of the random preference. Additionally, so…
A principled approach to network-based classification and data representation
2013
Measures of similarity are fundamental in pattern recognition and data mining. Typically the Euclidean metric is used in this context, weighting all variables equally and therefore assuming equal relevance, which is very rare in real applications. In contrast, given an estimate of a conditional density function, the Fisher information calculated in primary data space implicitly measures the relevance of variables in a principled way by reference to auxiliary data such as class labels. This paper proposes a framework that uses a distance metric based on Fisher information to construct similarity networks that achieve a more informative and principled representation of data. The framework ena…
Perceptually weighted optical flow for motion-based segmentation in MPEG-4 paradigm
2000
In the MPEG-4 paradigm, the sequence must be described in terms of meaningful objects. This meaningful, high-level representation should emerge from low-level primitives such as optical flow and prediction error which are the basic elements of previous-generation video coders. The accuracy of the high-level models strongly depends on the robustness of the primitives used. It is shown how perceptual weighting in optical flow computation gives rise to better motion estimates which consistently improve motion-based segmentation compared to equivalent unweighted motion estimates.
Computational Techniques for the Analysis of Small Signals in High-Statistics Neutrino Oscillation Experiments
2020
The current and upcoming generation of Very Large Volume Neutrino Telescopes – collecting unprecedented quantities of neutrino events – can be used to explore subtle effects in oscillation physics, such as (but not restricted to) the neutrino mass ordering. The sensitivity of an experiment to these effects can be estimated from Monte Carlo simulations. With the high number of events that will be collected, there is a trade-off between the computational expense of running such simulations and the inherent statistical uncertainty in the determined values. In such a scenario, it becomes impractical to produce and use adequately-sized sets of simulated events with traditional methods, such as M…
Adaptive variable structure fuzzy neural identification and control for a class of MIMO nonlinear system
2013
This paper presents a novel adaptive variable structure (AVS) method to design a fuzzy neural network (FNN). This AVS-FNN is based on radial basis function (RBF) neurons, which have center and width vectors. The network performs sequential learning through sliding data window reflecting system dynamic changes, and dynamic growing-and-pruning structure of FNN. The salient characteristics of the AVS-FNN are as follows: (1) Structure-learning and parameters estimation are performed automatically and simultaneously without partitioning input space and selecting initial parameters a priori. The structure-learning approach relies on the contribution of the size of the output. (2) A set of fuzzy r…
Can Dasymetric Mapping Significantly Improve Population Data Reallocation in a Dense Urban Area?
2016
The issue of reallocating population figures from a set of geographical units onto another set of units has received a great deal of attention in the literature. Every other day, a new algorithm is proposed, claiming that it outperforms competitor procedures. Unfortunately, when the new (usually more complex) methods are applied to a new data set, the improvements attained are sometimes just marginal. The relationship cost-effectiveness of the solutions is case-dependent. The majority of studies have focused on large areas with heterogeneous population density distributions. The general conclusion is that as a rule more sophisticated methods are worth the effort. It could be argued, however…
An efficient grid-based RF fingerprint positioning algorithm for user location estimation in heterogeneous small cell networks
2014
This paper proposes a novel technique to enhance the performance of grid-based Radio Frequency (RF) fingerprint position estimation framework. First enhancement is an introduction of two overlapping grids of training signatures. As the second enhancement, the location of the testing signature is estimated to be a weighted geometric center of a set of nearest grid units whereas in a traditional grid-based RF fingerprinting only the center point of the nearest grid unit is used for determining the user location. By using the weighting-based location estimation, the accuracy of the location estimation can be improved. The performance evaluation of the enhanced RF fingerprinting algorithm was c…
Dealing with risk: Gender, stakes, and probability effects
2015
This paper investigates how subjects deal with financial risk, both "upside" (with a small chance of a high payoff) and "downside" (with a small chance of a low payoff). We find that the same people who avoid risk in the downside setting tend to make more risky choices in the upside one. The experiment is designed to disentangle the probability-weighting and utility-curvature components of risk attitudes, and to differentiate settings in which gender differences arise from those in which they do not. Women are more risk averse for downside risks, but gender differences are diminished for upside risks.